MicroRNA Mediating Networks in Granulosa Cells Associated with...

Research ArticleMicroRNA Mediating Networks in Granulosa Cells Associatedwith Ovarian Follicular Development

Baoyun Zhang1 Long Chen1 Guangde Feng2 Wei Xiang1 Ke Zhang1

Mingxing Chu3 and Pingqing Wang1

1Bioengineering Institute of Chongqing University Chongqing China2Sichuan TQLS Animal Husbandry Science and Technology Co Ltd Mianyang China3Key Laboratory of Farm Animal Genetic Resources and Germplasm Innovation of Ministry of AgricultureInstitute of Animal Science Chinese Academy of Agricultural Sciences Beijing China

Correspondence should be addressed to Pingqing Wang wang pq21cncom

Received 14 October 2016 Revised 21 November 2016 Accepted 23 November 2016 Published 19 February 2017

Academic Editor Kang Ning

Copyright copy 2017 Baoyun Zhang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Ovaries which provide a place for follicular development and oocyte maturation are important organs in female mammalsFollicular development is complicated physiological progress mediated by various regulatory factors including microRNAs(miRNAs) To demonstrate the role of miRNAs in follicular development this study analyzed the expression patterns of miRNAsin granulosa cells through investigating three previous datasets generated by Illumina miRNA deep sequencing Furthermore viabioinformatic analyses we dissected the associated functional networks of the observed significant miRNAs in terms of interactingwith signal pathways and transcription factors During the growth and selection of dominant follicles 15 dysregulatedmiRNAs and139 associated pathways were screened out In comparison of different styles of follicles 7 commonly abundant miRNAs and 195pathways as well as 10 differentially expressed miRNAs and 117 pathways in dominant follicles in comparison with subordinatefollicles were collected Furthermore SMAD2 was identified as a hub factor in regulating follicular development The regulationof miR-26ab on smad2 messenger RNA has been further testified by real time PCR In conclusion we established functionalnetworks which play critical roles in follicular development including pivotal miRNAs pathways and transcription factors whichcontributed to the further investigation about miRNAs associated with mammalian follicular development

1 Introduction

Themammalian ovary is a dynamic organ The coordinationof follicle recruitment selection and ovulation and the timelydevelopment are essential for a functional ovary and fertility[1] Follicular development is a highly accurate orchestratedand periodic process which starts with the activation ofresting follicles gradually leading to the growth and selectionof dominant follicles (DFs) from small health follicles accom-paniedwith sequential and profounddifferentiation of oocyteand the surrounding somatic cells [2] especially granulosacells (GCs) [3] Understanding the molecular mechanism offollicular development is essential for unraveling the complexsynergies orchestrated during the process of forming thefertilizable ovum In an estrous cycle small follicular growth

is characterized by 2 or 3 successive follicular waves whichcoincide with the luteinizing hormone- (LH-) surge wavesDuring the waves a single follicle is selected normally thelargest (occasionally the largest two) which continuouslygrows as a DF while the others referring to subordinatefollicles (SFs) terminate development and undergo atresia[4] Both of the two kinds of follicles are named large healthyfollicles The complex transition from primordial folliclesto mature follicles is due to the functional differentiationand morphological transformation of GCs In this crucialperiod the growth of oocyte depends on the bidirectionalcommunication between oocyte and GCs [5 6] Hence theproliferation apoptosis and remarkable functional differen-tiation of GCs are significant events and required for folliclematuration [7] Each of these development steps involves

HindawiBioMed Research InternationalVolume 2017 Article ID 4585213 18 pageshttpsdoiorg10115520174585213

2 BioMed Research International

significant changes of follicular structure and functionrequiring accurate and coordinated adjustments to geneswhich have key roles in follicular selectionmaturation or thefollicle-luteal transition Any dysregulation in the expressionof these specific genes would be critical in determining thefate of DFs or SFs [8ndash11] In previous studies transcriptomeanalyses have identified some genes involved in folliculargrowth selection and maturation [12ndash14] However themolecular regulatory mechanisms at differential levels arestill unclear

Recently the posttranscriptional regulation dominatedby miRNAs has attracted extensive attention miRNAs regu-late gene expression via the combination of seed sequence andthe 31015840-untranslated region (UTR) of target mRNAs causingrepression of translation or degradation of the target mRNAsduring cell growth and differentiation [15] The expression ofmiRNA in the ovary varies with cell type function and stageof the estrous cycle miRNAs are involved in the formationof primordial follicles follicular recruitment and selectionfollicular atresia oocyte-cumulus cell interaction and GCfunction [1] Profiling studies of miRNA in ovarian tissueshave described the expression of miRNAs in the ovariesof various species [16ndash20] Conditional knockout (cKO) ofDicer1 from follicular GCs resulted in a number of ovarianfunctional defects including abnormal oocyte maturationdisrupted follicular development and ovulation increasedfollicular atresia and infertility [21ndash23] A single miRNAcould regulate follicle development during estrus cycle via acanonical pathway [24] in which the target gene of miRNAplays an important role Unsurprisingly many miRNAs alsocould target transcription factors (TFs) such as TGF-120573superfamily members follicle stimulating hormone receptor(FSHR) and luteinizing hormone receptor (LHR) whichhave been confirmed to have a connection with folliculardevelopment The abnormality of these molecules also led todysfunction of cellular communication and dysregulation ofnormal follicle development and recruitment [25ndash29] More-over several studies have demonstrated that the functions ofspecific miRNAs are implicated in different aspects of GCprocesses [30] such as proliferation [31ndash34] survival [35ndash37] terminal differentiation [38] steroidogenesis [31 33 3940] and cumulus expansion [41] in mammals For examplemiRNA-224 has been proved to be involved in transforminggrowth factor-beta-mediated mouse GCs proliferation andGC function by targeting smad4 [31] These results presentevidence that miRNA might be involved in the selectionof the DFs the mechanism of which has remained largelyelusive The complex nature of miRNA target interactionregulation and function however posed challenges forfunctional studies Whereas some miRNAs appear single-handedly to regulate specific signaling pathways most miR-NAs act in clusters and are fine tuners of cellular functionsIn most of previous studies results just demonstrated thefunction of a single miRNA in GCs In fact performingsignificant regulation of any biological process often resultsfrom complex regulating networks rather than one singlemiRNA Therefore an understanding of the mechanism ofaction of miRNA in follicular development requires globalcomprehension of the network of miRNA target interactions

within the milieux of other factors that dominate folliculardevelopment Hence profiling studies are important in orderto not only draw a spatial and temporal map of miRNAexpression in different follicles but also provide clues withregard to the function or regulation of miRNA

In this study according to 3 underused sequencingdatasets (GSE56002 GSE55987 and GSE54692) from GCs ofbovine we attempted to systematically dissect the complexsynergistic regulations of several functional miRNAs ratherthan a single miRNA in follicular development [42] basedon the networks of miRNAs-signal pathways and miRNAs-TFs AbundantmiRNAs and differentially expressedmiRNAswere identified and networks of miRNAs-signal pathwaysand miRNAs-TFs were constructed based on the correlationbetween miRNAs and predicted target genes Moreover bycalculating the degree of every node in networks hub playerswere identified to establish a centrical network from whichthe critical miRNAs pathways and TFs in the process offollicular development were identified The regulation of thesignificant miRNAs on hub genes would be further verifiedby RT PCR The results might provide novel insights intorevealing the potential mechanism ofmolecular regulation infollicular development in the context of miRNA synergisticregulatory networks

2 Materials and Methods

21 Differential Expression of miRNAs in GCs and DataNormalization A total of 64 differentially expressedmiRNAsin GCs were collected from the miRNA sequencing results ofSamuel Gebremedhnrsquos research group (GSE56002) [24] and52 ones from the study of another group Salilew-Wondimet al who also utilized Illumina small RNAseq (GSE55987)[47] Gebremedhn et al used miRDeep 2005 softwarepackage andDESeq2with a ldquohypothetical referencerdquo to screendifferentially expressed miRNAs in 6 ovarian follicle samples(3 biological replicates from DFs and others from SFs) at day19 of the estrous cycle in which the samples with externalsurface diameter ge 12mm were recognized as DFs whilethe ones le 11mm as SFs The study followed several cut-off criteria adjusted p value le 005 log2 fold change ge 1and false discovery rate (FDR) le 01 [24] Similarly Salilew-Wondim et al employed the analogous software andmethodsto analyze the differential expression of miRNAs under thesame criteria whichwere obtained from 12 granulosa samples(three biological replicates of GCs from SFs or DFs at day 3 orday 7 of the estrous cycle) [47] Briefly in this study follicleswith follicular diameter of 6mm (119899 = 43) were classifiedas SFs while follicles with a diameter of 8ndash10mm (119899 = 9)were considered as DFs at day 3 of the estrous cycle Onthe other hand at day 7 of the estrous cycle follicles witha diameter le 8mm (119899 = 58) were considered as SFs whilethose with 9ndash13mmdiameter (119899= 3) were categorized asDFsAlthough there are some biological differences between day3 and day 7 this did not exactly influence our analysis sincewhat we considered was the whole process of DFs and SFs Bycomparison abundantly expressed or dysregulated miRNAsin both datasets were dissected in this study Meanwhileanother dataset (GSE54692) which utilized microarray to

BioMed Research International 3

assess differentially expressed miRNAs in GCs of bovinewas investigated in the same manner and the miRNAsmeeting the same criteria mentioned above were selected[48] In summary after comparison of small and DFs wefirstly obtained 17 dysregulated miRNAs from the two typesof follicles Then 57 dysregulated miRNAs were identifiedbetween large atretic follicles and DFs Finally a total of 15miRNAs which played key roles in both growth and selectionphase ofDFswere further detected and analyzed in this paper

22 miRNA Target Gene Prediction and Relevant FunctionalAnalysis by GO and Pathway Enrichment There were noonline databases to predict the target genes of miRNAs inbovine In this context through sequence alignment weconfirmed that there was homology of miRNAs betweenhuman and bovine and since the prediction of target geneswas based on algorithm of sequence this study analyzedpatterns on the regulating functions of miRNAs in bovinefollicular development through their target prediction alongwith human species The potential target genes of differ-entially expressed miRNAs in GCs were acquired fromthe widely used online databases TargetScanHuman 70(httpwwwtargetscanorg) [49] with conservation (aggre-gate 119875CT gt 08) and context score (ltminus04 and percentilegt 85) and DIANA-microT (httpdianaimisathena-inno-vationgrDianaToolsindexphpr=microT CDSindex)[50]The aggregate 119875CT is calculated as

119875CT

= 1

minus ((1 minus 119875CT)site1 (1 minus 119875CT)site2 (1 minus 119875CT)site3 sdot sdot sdot)

(1)

In order to reduce false positives the predicted targetgenes which appeared at both databases were acceptedThusthe collection of predicted target genes of each obtainedmiRNA was imported into DIANA-mirPath (httpdianaimisathena-innovationgrDianaToolsindexphpr=mirpathindex) a miRNA-pathway analysis web server Each list ofcanonical pathways significantly affected by differentiallyexpressed miRNAs was made a contrast with another list andwe obtained the common pathways which were as targets ofdysregulated miRNAs All the following canonical pathwayswere identified from the Kyoto Encyclopaedia of Genes andGenomes (KEGG) databases

As a comprehensive set of functional annotation toolsDAVID (the Database for Annotation Visualization andIntegrated Discovery) has been used for integrative andsystematic analysis of enormous gene lists [51] GO termsare significantly overrepresented in a set of genes from threeaspects namely the biological process cellular componentand molecular function In this study the key GO biologicalprocess terms of the predicted target genes of miRNAs wereperformed using DAVID with the thresholds of enrichmentgene count gt 2 and p value lt 005

23 miRNA-Pathway Network and miRNA-TF NetworkConstruction Study on pathways associated with dysreg-ulated miRNAs was carried out using DIANA-mirPath

The results were integrated to get the intersection fromthose meeting p value threshold (Benjamini and HochbergrsquosFDR was applied with significant threshold set at p valuele 005) and microT threshold (08 of the score) Then theinteractions between miRNA and pathways were collectedto construct miRNA-pathway network Transcription factorsthat can be involved in control of particular ovarian functionswere screened from Animal Transcription Factor Database(httpwwwbioguoorgAnimalTFDBBrowseAllTFphpspe=Homo sapiens) and Sirotkinrsquos study [52] In order toimprove veracity target genes of miRNAs were predicted viadifferent software TFs which might be regulated by miRNAswere also identifiedThen the selected miRNAs-TFs databasewas used for constructing network by Cytoscape softwareunder the similar protocol [53] Furthermore throughcalculating the degree of each node hub TFs were selectedto construct the core network

24 Cell Culture and Transfection A steroidogenic humangranulosa-like tumor cell line (KGN) was undifferentiatedand maintained the physiological characteristics of ovariancells The KGN cells were cultured in DMEM basic (1x)highglucose medium (Gibco Life Technologies Carlsbad CAUSA) containing 12 fetal bovine serum (FBS Gibco Aus-tralia) and 1 antibiotics (100Uml penicillin and 100 120583gmlstreptomycin Sigma) in a humidified incubator at 370∘Cwith 5 CO

2 For human granulosa cells culture the GCs

were first purified as described previously [54] GCs werecultured at a final concentration of 5 times 105 viable cellsmlculture medium in 12-well plate at 370∘C and 5 CO

2

After 24 h the medium was replaced with RPMI only then4 120583g miR-26ab mimics inhibitors or miRNA expressionvectors pSUPER-miR-26ab [55] (with a negative control)were transfected using Lipofectamine 2000 The sequenceof miR-26ab mimics and miR-26ab inhibitors as well astheir negative controls (Genepharma Shanghai China) areas follows

miR-26amimics 51015840-UUCAAGUAAUCCAGGAUA-GGCU-31015840

miR-26a inhibitors 51015840-AGCCUAUCCUGGAUU-ACUUGAA-31015840

miR-26b mimics 51015840-UUCAAGUAAUUCAGG-AUAGGU-31015840

miR-26a inhibitors 51015840-ACCUAUCCUGAAUUA-CUUGAA-31015840

Mimics negative control 51015840-UUCUCCGAACGU-GUCACGUTT-31015840

Inhibitors negative control 51015840-CAGUACUUUUGU-GUAGUACAA-31015840

After 8 h the cells were subsequently treated with completemedium followed by extraction of total RNA from thecultured cells using Trizol (TaKaRa) at 48 h later

25 Real Time PCR Assay For RT PCR assays the cDNAwas synthesized from 1000 ng of purified RNA using the


Table 1 Fold changes of differentially expressed miRNAs in DFs compared with both small healthy follicles and SFs

miRNA ID DFs versus SHFs DFs versus SFsFold change Adj p value Fold change Adj p value

Downregulated miRNAs

miR-3178 minus360 0002 minus336 0001miR-1275 minus229 0020 minus228 0003

miR-625-3p minus221 0006 minus494 0001miR-3621 minus217 0002 minus221 0001

miR-483-3p minus217 0002 minus364 0001miR-1469 minus215 0014 minus511 0001miR-498 minus214 0003 minus369 0001miR-4279 minus205 0012 minus296 0001

Upregulated miRNAs

miR-202 418 0002 998 0001miR-876-5p 379 0002 599 0001

has-miR-876-3p 309 0002 392 0001miR-873-5p 270 0003 353 0001miR-451a 265 0014 249 0031miR-144-3p 235 0009 202 0032miR-652-3p 213 0003 350 0001

PrimeScript RT reagent kit (TaKaRa Bio Inc Otsu Japan)following the manufacturerrsquos instructions RT PCR was per-formed in an Applied Biosystems Step One RT PCR systemusing a SYBR Premix Ex Taq II Kit (Takara Bio Inc ShigaJapan) and RT PCR machine (Bio-Rad C1000PCR USA)Each sample was analyzed in triplicate and the experimentwas repeated three times The primers for smad2 miR-26amiR-26b U6 and 120573-actin are designed as follows

smad2 forward 51015840-AGAAGCAGCTCGCCAGCC-AG-31015840

smad2 reverse 51015840-CGGCGTGAATGGCAAGAT-GG-31015840

miR-26a stem-loop primer 51015840-CTCAACTGGTGT-CGTGGAGTCGGCAATTCAGTTGAGAGCCTA-TC-31015840

miR-26a forward 51015840-ACACTCCAGCTGGGTTCA-AGTAATCCAGGA-31015840

miR-26b stem-loop primer 51015840-CTCAACTGGTGT-CGTGGAGTCGGCAATTCAGTTGAGACCTAT-CC-31015840

miR-26b forward 51015840-ACACTCCAGCTGGGTTCA-AGTAATTCAGG-31015840

Universal reverse primer 51015840-TGGTGTCGTGGA-GTCG-31015840

120573-Actin forward 51015840-AAAGACCTGTACGCCAAC-AC-31015840

120573-Actin reverse 51015840-GTCATACTCCTGCTTGCT-GAT-31015840

U6 forward 51015840-CTCGCTTCGGCAGCACA-31015840

U6 reverse 51015840-AACGCTTCACGAATTTGCGT-31015840

PCR conditions were set as follows 95∘C for 30 sec followedby 40 cycles at 95∘C for 5 sec 60∘C for 35 sec and 95∘C for15 sec 60∘C for 1min and 95∘C for 15 sec as described pre-viously [31] Expression levels of smad2 and miR-26ab were

normalized to 120573-actin or U6 small nuclear RNA (snRNA)expression The data was analyzed by using the comparativeCT method [56]

26 Statistical Analysis All statistical analyses were per-formed by SPSS software version 170 (SPSS Inc ChicagoIL USA) and the results were shown as the mean plusmn standarddeviation (SD) of at least three biological replicates Thep values were determined by a 2-sided 119905-test and one-way ANOVA followed by the Tukeyrsquos post hoc test whichwas considered as the reference of statistically significantdifference

3 Results

31 Differentially Expressed miRNAs Detected in Both Growthand Selection Phases of DFs Follicular development is a com-plicated and elaborate process Both the growth and selectionof DFs are significant phases of the follicular developmentA prerequisite for understanding follicular progression isacquiring knowledge of its component interactions In orderto investigate the detailed spatiotemporal miRNA profilesduring follicular development from small healthy folliclesto large healthy follicles GEO repository (GSE54692) wasanalyzed in depth and the comparative results of differentfollicular groups (DFs versus small follicles and DFs versuslarge atretic follicles) demonstrated that there were 17 and57 miRNAs differentially expressed (larger than or equal totwofold adjusted p value le 005) between DFs and smallfollicles as well as between DFs and large atretic folliclesrespectively [48] Out of them 15 miRNAs (7 upregulatedmiRNAs and 8 downregulated miRNAs) were differentiallyexpressed in DFs compared to both small follicles and largeatretic follicles (Table 1) Then we used DIANA-mirPathand TargetScanHuman 70 to identify the target genes andaffected pathways associated with these 15 differentiallyexpressed miRNAs (S1 Table in Supplementary Materialavailable online at httpsdoiorg10115520174585213) This


Figure 1 Network of the common differentially expressed miRNAs and their functionally associated signaling pathways in DFs comparingwith both small healthy follicles and SFs The red squares represent the upregulated miRNAs while green squares represent downregulatedones The purple nodes represent pathways affected by two or three dysregulated miRNAs and the yellow nodes represent pathwayscoregulated by at least 4 dysregulatedmiRNAs Other pale blue circles represent pathways affected by only one differentially expressedmiRNAin DFs comparing with both small healthy follicles and SFs

network showed interaction between 7 upregulated as wellas 8 downregulated miRNAs and their identified 139 sig-naling pathways (Figure 1) Among them there were 29pathways coregulated by two or three dysregulated miRNAs7 pathways were identified to be influenced by at least fourdifferentially expressed miRNAs in DFs when comparingwith small healthy follicles or large atretic follicles (Figure 1)The concrete miRNAs which coregulated these 7 pathwayshave been showed in S2 Table For example MAPK signalingpathwaywas identified as a target ofmiR-873-5pmiR-144-3pmiR-625-3p miR-498 and miR-4279 while miR-3621 was a

special node without connections to any other pathway sinceour absent cognition about its potential function Taking intoconsideration that MAPK signaling pathways play a key rolein follicular function this result suggests the significance ofdifferentially expressed miRNAs

32 Abundance of miRNAs in GCs of DFs and SFs duringEstrous Cycle Since every step of the follicular developmentis important and worthy of investigation clarifying theprofile of miRNAs in the two main kinds of follicles is aburning problem due to miRNAsrsquo regulation process on gene


Table 2 (a) Summary of characteristics of miRNAs in DFs and SFs (b) The reads of top 10 abundant miRNAs in both DFs and SFs fromdifferent samples

(a)

Group Sample Number ofmapped reads

Reads aligned toknown miRNAs

Arithmetic meanof mapped reads

Arithmetic meanof known miRNAs

Ratio of knownmiRNAs

Dominant folliclesDFs1 599377 345689

6633387 3432217 05174DFs2 392924 255260DFs3 997715 428716

Subordinatefollicles

SFs1 861596 459794928373 467028 05031SFs2 939835 520377

SFs3 983688 420913

(b)

miRNA DFs miRNA SFsReads1 Reads2 Reads3 Reads1 Reads2 Reads3

miR-26a 48999 53635 42285 miR-26a 7773033 37599 61123miR-10b 2816867 46558 14742 miR-10b 62390 37494 63322miR-202 12209 4473 lt1000 miR-92a 1365333 8852 11115let-7a-5p 1083833 14314 10417 let-7f 13331 11065 11611let-7f 959533 14697 8616 miR-27b 1319467 12922 11789miR-22-3p 871033 3626 5359 miR-99b 1224133 18612 15768let-7i 869567 13802 7269 let-7a-5p 1100367 10133 10026miR-21-5p 869533 lt1000 36422 let-7i 973467 8944 11203miR-27b 847667 15893 20250 miR-191 8563 8073 9995miR-191 770033 15491 5147 miR-143 839767 3736 3906Oblique font represents identical miRNAs both in DFs and SFsReads1 the data were acquired from GSE56002Reads2 the data were acquired from Day 3 in GSE55987Reads3 the data were acquired from Day 7 in GSE55987

expression quantity which has been demonstrated by plentyof scientific evidence [57] As reported in the relevant GEOdatasets (GSE56002 and GSE55987) 6 miRNA sequencinglibraries were generated based on GCs detecting in bothDFs and SFs to understand the abundance and functionsof miRNAs in different follicular styles After filtering PCRprimers low-quality reads sequences shorter than 18 bpsand empty adaptors the mean quality reads of the biologicaltriplicates approximated 24 and 3 million in the libraries ofDFs and SFs respectively Sequence alignment of all readswhich met the criteria indicated that 663338 and 928373reads in DFs and SFs were mapped to the bovine referencegenome constituting 276 and 314 of the total qualityreads obtained respectively Furthermore 343221 reads inDFs and 467028 in SFs were similar to known bovinemiRNAs reported in miRbase release 20 (Table 2(a))

Based on the sequencing results several miRNAs werecommonly abundant in both datasets Comparing the top10 abundantly expressed miRNAs in each group miR-26amiR-10b let-7 families (let-7a-5p let-7f and let-7i) miR-27b and miR-191 were consistently observed in both DFsand SFs (Table 2(b)) To sum up the network indicated thatthese abundantly expressed miRNAs might play key roles inmaintaining the normal physiological function in DFs as wellas SFs

33 Canonical Pathways Associated with the Top 7 AbundantlyExpressed miRNAs in GCs of DFs and SFs In order tounderstand the functional involvement of the 7 commonmiRNAs in follicular development target genes of eachmiRNAwere predicted and the relational canonical pathwayswere performed by mirPath As a result a total of 195canonical pathways were affected by the predicted targetgenes of highly expressed miRNAs (S3 Table) There were44 pathways regulated by at least 2 different miRNAs amongwhich 16 pathways were coregulated by more than 3 miRNAs(Figure 2) Thereinto MAPK is an important signaling path-way in cell proliferation and may function in granulosa celldeath and follicular atresia [58] It was comodulated by all the7miRNAs includingmiR-26a miR-10b let-7 families (let-7a-5p let-7f and let-7i) miR-27b and miR-191 To understandthe regulationmechanism ofmiRNAs in theMAPK signalingpathway target genes for the synergic miRNAs were iden-tified Deserved to be mentioned the let-7 families regulatethe 6 genes and miR-27b targets 8 genes in MAPK pathway(Table 3) These target genes spread in the different positionsof MAPK signaling to influence various functional modulesand further establish interactions with other pathways suchas Wnt signaling pathway (Figure 3) Therefore it speculatedthat these miRNAs regulate some processes of folliculardevelopment through modulating MAPK signaling pathway


Figure 2 Network of abundantly expressed miRNAs and correlative pathways in both DFs and SFs Yellow nodes represent abundantlyexpressed miRNAs in common while blue nodes represent the pathways affected by miRNAs

Table 3 Target genes regulated by top 7 abundantmiRNAs involvedin MAPK signaling pathway

miRNA ID Target genesmiR-26a TAB2 NLK MEF2C PAK1miR-10b MAX MEF2C RAP1Alet-7a-5p FLNA NGF FAS MEF2C CASP3 RASGRP1let-7f FLNA NGF FAS MEF2C CASP3 RASGRP1let-7i FLNA NGF FAS MEF2C CASP3 RASGRP1

miR-27b EGFR TAB2 NLK NF1 FAS STMN1 MEF2CGRB2

miR-191 BDNF

34 Canonical Pathways Affected by Differentially ExpressedmiRNAs in GCs of DFs Compared with SFs According tothe comparison of the two sequencing datasets from GEO(GSE56002 and GSE55987) there were 10 miRNAs signifi-cantly differentially expressed in GCs of DFs compared withSFs of which 5 maturedmiRNAs namely miR-183 miR-34cmiR-708 miR-21-3p andmiR-221 were significantly upregu-lated in DFs while the others including miR-409a miR-335miR-449a miR-214 and miR-224 were significantly lowerexpressed (S4 Table) The overall log2 fold change valuesranged from minus164 (miR-409a) up to 703 (miR-183) We alsoused DIANA-mirPath v20 software and TargetScanHuman70 to identify target genes and regulatory pathways of dif-ferentially expressed miRNAs were compared and analyzed


MAPK signaling pathway

Classical MAP kinasepathway CACN

NGFBDNFNT34EGFFGF FGFR

EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP

HeterotrimericG-protein IP3cAMP

DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos

Phosphatidylinositol signaling system

NIKIKK

TauSTMN1cPLA2

MNK12RSK2MP1Scaffold

MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos

Proliferationdifferentiation

NFBProliferationinflammationantiapoptosis

TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK

NFAT-2NFAT-4c-JUNJunD

ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB

p53 signalingpathway

Wnt signalingpathway

ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3

Serum cytotoxic drugsirradiation heat shock

reactive oxygen specieslipopolysaccharide

and other stress

ERK5 pathway

Serum EGFreactive oxygen species

or tyrosine kinase downstream

MEK5 ERK5 Nur77

MAPKKKK MAPKKK MAPKK MAPK Transcriptionfactor


+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS

JNK and p38 MAP pathwaykinase

Ca2+

04010 102315(c) Kanehisa Laboratories

Proliferationdifferentiationinflammation

c-Myc

Scaffold

Figure 3 MAPK signaling pathway This map of MAPK signaling pathway was obtained based on KEGGThe yellow boxes represent targetgenes which were regulated by the 7 critical miRNAs identified by previous analysis

using the same method (S5 Table) There were 31 pathwayscoregulated by two or three dysregulated miRNAs suchas Adherens junction and PI3K-Akt signaling respectively(Figure 4) while there were 16 pathways coregulated byat least 4 dysregulated miRNAs such as TGF-120573 signalingpathway TGF-120573 signaling pathway has been demonstrated toplay a crucial role in the local modulation of cell-cell commu-nication [59] Thus TGF-120573 signaling pathway might exhibitregulatory function for human GCs in ovarian physiologySpecifically considering that the influences of miRNAs onsignaling pathways were achieved by manipulating relevantgenes involved in signaling pathways genes in the TGF-120573 signaling pathway regulated by miRNAs or in a com-plex miRNAsrsquo combination were illustrated in Table 4 Forexample miR-335 could regulate 7 genes namely DCN FSTTHBS1 RBL1 ACVR2A LTBP1 and BMPR2 while THBS1was also regulated by miR-708 where the two miRNAs haddifferent regulated directions in DFs (Figure 5) Becauseof the synergetic regulation of several significant miRNAs

TGF-120573 signaling pathway might be closely related to follic-ular development Besides a single differentially expressedmiRNA might regulate several pathways simultaneouslyAll of these complex relations between miRNAs and theirmodulating pathways thus form a functional network relatedto the different periods of estrous cycle

35 GO Functional Enrichment Analysis of the Pivotal miR-NAs Based on the above findings GO analysis seems tobe meaningful with respect to the function of miRNAs onfollicular development process especially the miRNAs withhigh abundance and significantly differentially expressedmiRNAs which could be recognized as the pivotal miRNAsAfter screening the target gene prediction of the pivotalmiRNAs with the thresholds of certain119875CT and context score696 genes were identified as the functional target genes Byemploying the DAVID software a total of 260 GO functionitems were enriched Among them 206 were enriched in bio-logical process (BP) 20 in cellular component (CC) and the


Figure 4 Network of signal pathways and their respective dysregulated miRNAs in DFsThe red squares represent the upregulated miRNAswhile the green squares represent downregulated ones The purple nodes represent pathways affected by two or three dysregulated miRNAsand the yellow nodes represent pathways coregulated by at least 4 dysregulated miRNAs Other pale blue circles represent pathways affectedby only one differentially expressed miRNA in DFs comparing with SFs

Table 4 Target genes regulated by differentially expressed miRNAsin TGF-120573 signaling pathway

miRNA ID Target genesmiR-708 THBS1miR-21-3p TGIF1 SP1miR-409a PITX2 BMPR2miR-335 DCN FST THBS1 RBL1 ACVR2A LTBP1 BMPR2miR-224 SMAD4 LTBP1 BMPR2miR-214 CHRD ACVR2A

others inmolecular function (MF)The top 5 of the significantGO terms (with the smallest p value) in each category wereshown in Table 5 Interestingly in BP the top 5 functions

are correlative with embryonic development It suggestedthat these miRNAs and target genes participated in not onlyfollicular development but also embryonic development

36 The miRNA-TFs Coregulatory Network in DFs and SFsBased on the hypothesis that the complexity of the eukaryotictranscriptional regulation machinery reflects a multitudeof responses and that regulatory axes involving miRNAsand TFs are not isolated instances the predicted TFs wereincorporated along with the differentially expressed miRNAsin a transcriptional network Corresponding to the total pre-dicted genes of the pivotalmiRNAs in follicular developmenta total of 31 transcription factors involved in control of par-ticular ovarian functions retrieved from published scientificreports were collected Then the regulating network between


Table 5 The top 5 GO terms enriched by the pivotal miRNAs

Category1 Term Description Count2 p value3

BP

GO0048598 Embryonic morphogenesis 34 17119864 minus 10

GO0035113 Embryonic appendage morphogenesis 16 38119864 minus 8

GO0030326 Embryonic limb morphogenesis 16 38119864 minus 8

GO0043009 Chordata embryonic development 31 63119864 minus 8

GO0009792 Embryonic development ending in birth or egg hatching 31 77119864 minus 8

CC

GO0005667 Transcription factor complex 19 200119864 minus 05

GO0044451 Nucleoplasm part 32 140119864 minus 04

GO0005654 Nucleoplasm 44 170119864 minus 04

GO0005626 Insoluble fraction 41 450119864 minus 04

GO0005624 Membrane fraction 39 820119864 minus 04

MF

GO0003700 Transcription factor activity 53 260119864 minus 05

GO0016563 Transcription activator activity 28 960119864 minus 05

GO0030528 Transcription regulator activity 71 990119864 minus 05

GO0043565 Sequence-specific DNA binding 35 290119864 minus 04

GO0003705 RNA polymerase II transcription factor activityenhancer binding 7 940119864 minus 04

Notes 1GO function category 2the number of target genes involved in the GO terms 3p values have been adjusted using the BenjaminindashHochberg methodBP biological process CC cellular component MF molecular function GO Gene Ontology

Chordin Noggin BAMBI

BMPRIBMPRIIDAN BMP

Smadl58

Smad4Growth factor RasMAPK ERK

DNA

DNA

DNA

DNA

DNA

DNAId

Osteoblast differentiationneurogenesis

ventral mesodermspecification

TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12

Decorin TGFTGF RITGF RII

Smad23

SARA Smad4

Transcription factorscoactivators

and corepressors

p107E2F45

DP1c-Myc

Angiogenesisextracellular matrix

neogenesisimmunosuppressionapoptosis induction

Apoptosis

Ubiquitinmediated

proteolysis TGIF

p300 p15SP1 G1 arrest

Cell cycleTAK1 MEKK1

DAXXJNK MAPK signalingpathway

RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2

Gonadal growthembryo differentiationplacenta formation etc

Left-right axis determinationMesoderm and

endoderm induction etc

+p

+p

+p

+p

+p

+p

minusp

+u +u

TGF- signaling pathway

IFN

Skp1

p70S6K


Figure 5 TGF-120573 signaling pathway This map of TGF-120573 signaling pathway was based on KEGG where the red boxes represent target genesregulated by significantly differentially expressed miRNAs through predicting results


SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335

miR-10bmiR-27bmiR-34c

miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)

Figure 6 Network of miRNAs and TFs (a) Network of TFs and pivotal miRNAs confirmed in comparison of DFs and SFs (b) The corenetwork shrank by extracting the hub TFs from (a) The red nodes represent abundantly expressed miRNAs both in DFs and SFs The yellownodes represent upregulated and the green nodes represent downregulated miRNAs The pink rhombic nodes represent TFs affected bydifferentially expressed miRNAs (c) Network of TFs and critical miRNAs confirmed in comparison of DFs versus SFs as well as DFs versussmall follicles (d) The relevant core network constructed by the relations between the hub TFs and miRNAs with correspondence to (c)The red nodes represent upregulated miRNAs and green nodes represent downregulated miRNAs The purple rhombic nodes represent TFsaffected by both differentially expressed miRNAs The orange lines display the connections of TFs and miRNA which had evidenced basis[43ndash46]

14miRNAs and 30TFswas extracted (Figure 6(a)) SomeTFsreferring to SMAD2 SMAD3 SMAD4 SMAD5 and Ptch1have been affected by the most miRNAs with respect to theirhighest degrees in the network Since the critical significance

of the TFs modulated by multiple miRNAs the hub TFsrecognized as carrying degree larger than 2 (S6 Table) weredetermined and a shrunk miRNA-TF regulatory networkonly covering miRNAs and the hub TFs was subsequently


Adherens junction

FoxO signaling pathway

Hippo signaling pathway

miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection

Signaling pathways regulatingpluripotency of stem cells

Pancreatic cancer

Colorectal cancer

Chagas disease(American trypanosomiasis)

miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b

AGE-RAGE signaling pathwayin diabetic complications

Cell cycle

Pathways in cancer

SMAD2


Figure 7 Network of SMAD2 and relevant pathways regulated by identified miRNAs The yellow circular nodes represent highly abundantmiRNAs both in DFs and SFs Red circular nodes represent the upregulated miRNAs in DFs and the green circular nodes represent thedownregulated miRNAs in DFs The red and green triangular nodes represent up- and downregulated miRNAs in DFs when compared witheither small healthy follicles or SFs respectively The purple square nodes represent pathways regulated by these identified miRNAs andSMAD2 simultaneously

generated (Figure 6(b)) Similarly a network consisting of35 TFs and several dysregulated miRNAs obtained from thecomparison of DFs versus small healthy follicles and DFsversus SFs was constructed (Figure 6(c)) in which STAT3and SMAD2 showed prominent performance in terms oftheir highest connections withmiRNAs (5miRNAs for each)Moreover 21 TFs were regulated by downregulated miRNAsalone while only 3 TFs were regulated by upregulated miR-NAs alone Similarly the relevant shrunk network coveringthe 11 hub TFs (with degree larger than 2 S7 Table) hasbeen constructed to represent the core miRNA-TF regulatoryrelations (Figure 6(d)) SMAD2 might play a key role infollicular development because of its participation in both thecore miRNA-TF networks as shown in Figures 6(b) and 6(d)The network of predicted TFs and miRNAs indicated thepossible transcriptional regulation in follicular development

SMAD superfamily including SMAD1 SMAD2 SMAD3SMAD4 and SMAD5 have been demonstrated to havefunctional correlations with ovarian follicular growth andselection [60ndash62] SMAD2 could be regulated by all theidentified importantmiRNAs fromdifferent detecting groupsin our study We found that TGF-120573 signaling pathwaywould be regulated by several miRNAs related to folliculardevelopment such asmiRNA-21-3pwhile it alsowasmediatedby SMAD superfamily [63] There is a group of miRNAsthat could coregulate both some signaling pathways (such

as TGF-120573 signaling pathway) and SAMD2 Interestingly inthese identified pathways regulated by miRNAs SMAD2frequently affects the activity of these pathways as a keyfunctional component (Figure 7) In conclusion SMAD2could be considered as a bridge connecting predecessorsand successors and affecting pathway activity in responseto environmental signals The result also suggested that inovarian follicular development different regulatory elementsfunctioned synergistically in networks rather than workingalone

37 The Regulatory Impact of miR-26ab on the Expressionof smad2 in KGN Cells As the above results of this studywe deduced that some miRNAs may influence folliculardevelopment process through implementing regulation onsome genes and associated signaling pathways for instancethe TF smad2 However it was primary prediction basedon the importance on its functional networks and fewevidences for the prediction were provided by experimentalresearches A related research reported that miR-26b couldinduce apoptosis in GCs by targeting SMAD4 both directlyand indirectly through USP9X which regulated the ubiq-uitination of SMAD4 [63 64] Since miR-26b and miR-26aare highly homologous and in many species of mammals theseed sequences are also highly conservative (Figure 8(a))we conducted the investigation of the regulatory function


HumanChimpRabbit

CowmiR-26amiR-26b

U C G G A U A G G A C C U A A U G A A C U U

U G G A U A G G A C U U A A U G A A C U U

--CU U U U U CU UACU U G A G A A CU U GU A AU--


--C C U U U AU U UACU U G A G A A CU U GU A AU--

--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6

pSUPER-miR-26apSUPER-miR-26b

(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+

miR-26a mimicmiR-26a inhibitor

smad2

(d)

lowast

minus minus

minus minus

+

+

miR-26b mimicmiR-26b inhibitor

00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)

Figure 8The effect of miR-26ab on the regulating smad2mRNA in KGN cells (a) A sketchmap describes predicted seed sequences of miR-26ab in the conservative 31015840-UTR of smad2 in several mammal species (b)The transfection efficiency of overexpression vectors of miR-26ab(pSUPER-miR-26a and pSUPER-miR-26b) was validated by RT PCR (c d and e) The effects of pSUPER-miR-26ab miR-26ab mimicsand miR-26ab inhibitors on the smad2mRNA level were identified in KGN cells respectively lowast119901 lt 005 lowastlowast119901 lt 001 and lowastlowastlowast119901 lt 0001 allexperiments were independently repeated three times


of the miR-26ab on smad2 The miRNA overexpressionvectors miR-26ab mimics and miR-26ab inhibitors weretransfected into KGN cells successively The results showedthat overexpression of miR-26ab in KGN cells (Figure 8(b))led to the significant suppression of smad2 (Figure 8(c))Cells transfected with miR-26ab mimics displayed a signifi-cantly decreased expression of smad2 In contrast the miR-26a inhibitor transfected cells had an obviously increasedtendency of smad2 expression comparedwithNC transfectedcells (Figures 8(d) and 8(e)) It suggested that miR-26abcould regulate the expression of smad2 inKGNcell lineHow-ever whether miR-26ab could directly target SMAD2 needsfurther research Thus this experiment probably providespreliminarily supportive evidence on our speculative effortsIn this context other important regulating relations amongmiRNAs as well as genes and signaling pathways related tofollicular development which were identified by our analysismay be worth studying in depth

4 Discussion

Follicular development during the estrous cycle is an extraor-dinarily complex and synergistic process which might beregulated accurately by plenty of regulatory factors such asmiRNAs and TFs The aim of this study was to analyzethe function of significant miRNAs macroscopically andassociated functional networks related to follicular devel-opment via bioinformatic investigation It is worth notingthat miRNAs are largely conserved in different species ofmammal Furthermore studies of miRNAs in ovarian tissueshad confirmed the similar expression patterns in ovariesof various species including humans [16] mice [17 5765] pigs [18] sheep [66] goats [19] and cows [20 67ndash69] Through these references and related data miRNAswhich were discovered in transcriptome of bovine are alsosubsistent in humans and mice Therefore it is feasiblethat TargetScanHuman and DIANA which are developedmainly for human also could be used to predict targetgenes of differentially expressed miRNAs in bovine becauseof sequence conservation and the relevant algorithm basismiRNA deep sequencing quantifies the relative abundance ofmiRNAs by their frequencies in terms of read counts Highlyabundant miRNAs have higher likelihood of higher readcounts compared to miRNAs with lower abundance [70] InGSE56002 from all reads thatmet the quality control criteria343221 reads in DFs and 467028 in SFs were found to besimilar to known miRNAs reported in miRbase [24] Amongthe detected miRNAs which appeared in both GSE56002 andGSE55987 lots of miRNAs such as isoforms of let-7 familywere commonly expressed with high levels in both DFs andSFs It implied that this kind of miRNAs might not regulateselection of DFs butmaintain normal physiological functionsin GCs of both DFs and SFs during the estrous cycle Theprevious studies had demonstrated that the let-7 family couldregulate steroidogenesis and expression of steroidogenesis-related genes [71] In fact steroidogenesis is a crucial biologyprocess for maintaining normal physiology function in bothDFs and SFs Not only let-7 family but also miR-191 and miR-26a present abundant expression which could increase the

proliferation of GCs [72] and regulate gonad developmentpartially through its target on exm2 [73] Specifically miR-26a showed abundant expression in both DFs and SFswhile the reads of miR-26a screened in SFs were actuallymore than in DFs The results indicated that miRNA-26amight play an important role in discrepant functions betweenSFs and DFs Furthermore the canonical pathways suchas PI3K-Akt signaling pathway MAPK signaling pathwayTGF-120573 signaling pathwayWnt signaling pathways andAxonguidance which were enriched from abundant miRNAs alsorelated to cell metabolism and signal transduction in normalfollicular development It demonstrated that the functions ofthese regulated pathways were of equal importance in dif-ferent follicular types Some research articles have suggestedEGFR MEF2C and BDNF in MAPK signaling pathwaywere regulated bymiR-27b andmiR-191 respectively [74ndash77]Meanwhile it has been demonstrated that let-7 family mightbe involved in the estrous cycle through MAPK signalingpathway [78ndash80]

Abundantly expressed miRNAs might have key roles inmaintaining the normal status of follicles while differentiallyexpressed miRNAs would exhibit more regulatory functionsin follicular growth selection and the fate of DFs and SFsA total of 10 miRNAs were dysregulated between DFs andSFs and the result might provide valuable insights into theirpotential roles in folliculogenesis in a stage-dependent man-ner Thus it could be assumed that several signal pathwaysinfluenced by differentially expressed miRNAs were associ-ated with growth and selection of follicles Previous studiesreported that increased cell apoptosis would be observed inGCs transfected with the miR-21 inhibitor Furthermore thecritical roles of miR-21 in regulating follicular developmentand preventing GCs apoptosis in DFs had also been verified[35] while miR-183 upregulated in DFs might induce cellapoptosis [72] It suggested that in follicular developmentmultiple miRNAs pathways or TFs work simultaneouslythough they might show some opposite effects In additionSMAD4 which played a key role in TGF-120573 pathway wouldbe targeted by miR-224 [31] while miR-214199a and miR-335 could affect TGF-120573 pathway in different manners [81 82]TGF-120573 superfamily members have been implicated in regu-lating GC proliferation [83] and terminal differentiation [84]that are critical for normal ovarian follicular developmentFurthermore by GO functional enrichment we found thatthe miRNA target genes played key role in follicular devel-opment which can also effect the embryonic developmentIt is well known that follicular development and embryonicdevelopment are both two important biological processes forreproduction The roles of some miRNA target genes in boththese processes were probably similar For instance the genesin Wnt signaling pathway were regulated by same miRNAsin both follicular development and embryonic development[46]

miRNAs participate in follicular development not only inone single manner there is another primary mode to com-mand maturation of follicles related to critical transcriptionfactors Similar to the significance of pathway regulationTFs also could influence the regulatory network in mediat-ing follicular development According to the bioinformatic


analysis SMAD2 might be coregulated by miR-27b miR-10b and miR-26a which were expressed abundantly in bothfollicle types miR-21 and miR-409a with crosscurrent inDFs also could regulate smad2 Interestingly among thesemiRNAs miR-21 was demonstrated to be regulated viaSMAD23 signaling [85] It suggested that SMAD2 interactedwith some miRNAs and played key roles in follicular devel-opment miR-26a and miR-26b are highly homologous andthe seed regions are highly conservative in several speciesIn our study we concluded that miR-26ab could decreasethe mRNA expression of smad2 through RT PCR resultsNevertheless the detailed regulatory mechanisms need to befurther studied Because of the abundance of miR-26 bothin DFs and in SFs smad2 expression may be in a low leveland the correlation pathways may be in an inactive statusMoreover smad2 was also coregulated by miR-498 miR-3178 miR-4279 andmiR-625-3p which were downregulatedand miR-876-3p that was upregulated in DFs comparedwith both small follicles and SFs Although the complexcorrelation of SMAD2 and significant miRNAs made thisTF a hub in the whole gene regulatory network of follic-ular development deficient evidence about the functionalrelations of SMAD2 and miRNAs was obviously scarce toconfirm this description The functions of SMAD2-miRNAsnetwork in follicular development need further study BesidesSMAD2 other members of SMAD superfamily such asSMAD3 or SMAD4 were also demonstrated to be associatedwith miRNAs and signaling pathways [31 86] especiallyTGF-120573 signaling pathway which had illustrated affectingovary development [87] For example miR-21 could regulatethe expression of SMAD7 and TGF-1205731 [88] The accuratelyregulatory network composed of importantmiRNAs and hubTFs would provide a valuable perspective for understandingthe formation of DFs during estrous cycle

Precisely because of themiscellaneous connection amongmiRNAs signaling pathways and TFs the regulatory net-work in final maturation of follicle and preparation for thesubsequent follicle-luteal transitionwould bemore thoroughOur coregulatory network will help to draw the dynamicchanges ofmiRNAs and associated regulatorymodules acrossa wide range of follicular developmental stages Howeverthere were also some deficiencies in this study The workwas not based on the relationship of miRNAs and hormoneswhich play a key role in the whole estrous cycle SeveralmiRNAs were demonstrated to be regulated by hormonessuch as luteinizing hormone (LH) hCG (human chorionicgonadotropin) and follicle stimulating hormone (FSH) [3135 43 89] which displayed important controls on ovarianfunctions It suggested that miRNAs may regulate ovarianfunctions associated with changes of hormones contentMoreover although the significant miRNAs and their influ-encing pathways or TFs were identified the functions ofdifferentially expressed miRNAs in follicular developmentwere still unclear Despite these limitations this study stillpredicted possible details about molecular regulation net-work and identified probable key regulators in the processof follicular development which provided a novel idea tounderstand the regulation of follicular development deeplyas well as diagnosis and treatment for infertility

5 Conclusions

In this study via bioinformatic analysis we concluded thatduring the growth and selections of DFs lots of miRNAs inGCs which are abundantly expressed (let-7) or dysregulated(miR-21-3p) take part in biology processes by forming net-works with TFs (such as SMAD superfamily) and pathways(TGF-120573 signaling pathway) By GO functional enrichmentanalysis of the pivotal miRNAs target genes 260 GO functionitems in BP CC and MF were enriched SMAD2 regulatedby miR-26ab has been demonstrated by RT PCR as one ofthese kinds of TFs may play a key role in several pathwaysas a participator It suggested that miR-26ab-SMAD2-TGF-120573 signaling pathway might play a significant role in folliculardevelopment as an axis Having said that we wish to empha-size that the functions of other pivotal miRNAs TFs andpathways need more studies at macro level

Disclosure

Baoyun Zhang and Long Chen are co-first authors

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this article

Acknowledgments

This work was supported by the National Natural Sci-ence Foundation of China (Grant no 31372287) Min-istry of Agriculture Transgenic Major Projects of China(2014ZX0800952B) the Agricultural Science and TechnologyInnovation Program of China (ASTIP-IAS13) and NationalBiological Breeding Capacity Building and IndustrializationProjects (2014-2573) The authors want to take this oppor-tunity to acknowledge all the projects for their supportand participation They also would like to acknowledge allsequencing datasets in this study

References

[1] S W Maalouf W S Liu and J L Pate ldquoMicroRNA in ovarianfunctionrdquoCell and Tissue Research vol 363 no 1 pp 7ndash18 2016

[2] P G Knight and C Glister ldquoPotential local regulatory functionsof inhibins activins and follistatin in the ovaryrdquo Reproductionvol 121 no 4 pp 503ndash512 2001

[3] F Tu Z X Pan Y Yao et al ldquomiR-34a targets the inhibin beta Bgene promoting granulosa cell apoptosis in the porcine ovaryrdquoGenetics and Molecular Research vol 13 no 2 pp 2504ndash25122014

[4] O J Ginther M C Wiltbank P M Fricke J R Gibbons andK Kot ldquoSelection of the dominant follicle in cattlerdquo Biology ofReproduction vol 55 no 6 pp 1187ndash1194 1996

[5] R Buccione A C Schroeder and J J Eppig ldquoInteractionsbetween somatic cells and germ cells throughout mammalianoogenesisrdquo Biology of Reproduction vol 43 no 4 pp 543ndash5471990


[6] J M J Aerts and P E J Bols ldquoOvarian follicular dynamicsa review with emphasis on the bovine species Part I follicu-logenesis and pre-antral follicle developmentrdquo Reproduction inDomestic Animals vol 45 no 1 pp 171ndash179 2010

[7] H Yada K Hosokawa K Tajima Y Hasegawa and F KotsujildquoRole of ovarian theca and granulosa cell interaction in hor-mone production and cell growth during the bovine follicularmaturation processrdquo Biology of Reproduction vol 61 no 6 pp1480ndash1486 1999

[8] M J Canty M P Boland A C O Evans and M A CroweldquoAlterations in follicular IGFBP mRNA expression and follicu-lar fluid IGFBP concentrations during the first follicle wave inbeef heifersrdquo Animal Reproduction Science vol 93 no 3-4 pp199ndash217 2006

[9] A C O Evans J L H Ireland M EWinn et al ldquoIdentificationof genes involved in apoptosis and dominant follicle develop-ment during follicular waves in cattlerdquo Biology of Reproductionvol 70 no 5 pp 1475ndash1484 2004

[10] T Fayad V Levesque J Sirois D W Silversides and J GLussier ldquoGene expression profiling of differentially expressedgenes in granulosa cells of bovine dominant follicles usingsuppression subtractive hybridizationrdquo Biology of Reproductionvol 70 no 2 pp 523ndash533 2004

[11] M Mihm P J Baker L M Fleming A M Monteiro and P JOrsquoShaughnessy ldquoDifferentiation of the bovine dominant folliclefrom the cohort upregulates mRNA expression for new tissuedevelopment genesrdquo Reproduction vol 135 no 2 pp 253ndash2652008

[12] I Gilbert C Robert S Dieleman P Blondin andM-A SirardldquoTranscriptional effect of the LH surge in bovine granulosa cellsduring the peri-ovulation periodrdquo Reproduction vol 141 no 2pp 193ndash205 2011

[13] J U Rao K B Shah J Puttaiah and M Rudraiah ldquoGeneexpression profiling of preovulatory follicle in the buffalocow effects of increased IGF-I concentration on periovulatoryeventsrdquo PLoS ONE vol 6 no 6 Article ID e20754 2011

[14] L K Christenson S Gunewardena X Hong M Spitschak ABaufeld and J Vanselow ldquoResearch resource preovulatory LHsurge effects on follicular theca and granulosa transcriptomesrdquoMolecular Endocrinology vol 27 no 7 pp 1153ndash1171 2013

[15] E Huntzinger and E Izaurralde ldquoGene silencing by microR-NAs contributions of translational repression and mRNAdecayrdquo Nature Reviews Genetics vol 12 no 2 pp 99ndash110 2011

[16] Y Liang D Ridzon LWong andC Chen ldquoCharacterization ofmicroRNA expression profiles in normal human tissuesrdquo BMCGenomics vol 8 article 166 2007

[17] S Ro R Song C Park H Zheng K M Sanders and W YanldquoCloning and expression profiling of small RNAs expressed inthe mouse ovaryrdquo RNA vol 13 no 12 pp 2366ndash2380 2007

[18] M Li Y Liu T Wang et al ldquoRepertoire of porcine microRNAsin adult ovary and testis by deep sequencingrdquo InternationalJournal of Biological Sciences vol 7 no 7 pp 1045ndash1055 2011

[19] Y-H Ling C-H Ren X-F Guo et al ldquoIdentification andcharacterization of microRNAs in the ovaries of multiple anduniparous goats (Capra hircus) during follicular phaserdquo BMCGenomics vol 15 article 339 2014

[20] M Hossain N Ghanem M Hoelker et al ldquoIdentification andcharacterization of miRNAs expressed in the bovine ovaryrdquoBMC Genomics vol 10 article 1471 p 443 2009

[21] X Hong L J Luense L KMcGinnisW B Nothnick and L KChristenson ldquoDicer1 is essential for female fertility and normal

development of the female reproductive systemrdquoEndocrinologyvol 149 no 12 pp 6207ndash6212 2008

[22] A K Nagaraja C Andreu-Vieyra H L Franco et al ldquoDeletionof dicer in somatic cells of the female reproductive tract causessterilityrdquo Molecular Endocrinology vol 22 no 10 pp 2336ndash2352 2008

[23] G Gonzalez and R R Behringer ldquoDicer is required for femalereproductive tract development and fertility in the mouserdquoMolecular Reproduction and Development vol 76 no 7 pp678ndash688 2009

[24] S Gebremedhn D Salilew-Wondim I Ahmad et alldquoMicroRNA expression profile in bovine granulosa cellsof preovulatory dominant and subordinate follicles during thelate follicular phase of the estrous cyclerdquo PLoS ONE vol 10 no5 Article ID e0125912 2015

[25] B Bao and H A Garverick ldquoExpression of steroidogenicenzyme and gonadotropin receptor genes in bovine folliclesduring ovarian follicular waves a reviewrdquo Journal of AnimalScience vol 76 no 7 pp 1903ndash1921 1998

[26] U A Vitf M Hayashi C Klein and A J W Hsueh ldquoGrowthdifferentiation factor-9 stimulates proliferation but suppressesthe follicle-stimulating hormone-induced differentiation of cul-tured granulosa cells from small antral and preovulatory ratfolliclesrdquo Biology of Reproduction vol 62 no 2 pp 370ndash3772000

[27] L J Spicer N B Schreiber D V Lagaly P Y Aad L B Douthitand J A Grado-Ahuir ldquoEffect of resistin on granulosa and thecacell function in cattlerdquo Animal Reproduction Science vol 124no 1-2 pp 19ndash27 2011

[28] K-G Hayashi K Ushizawa M Hosoe and T TakahashildquoDifferential genome-wide gene expression profiling of bovinelargest and second-largest follicles identification of genes asso-ciated with growth of dominant folliclesrdquo Reproductive Biologyand Endocrinology vol 8 article 11 2010

[29] B Sisco L J Hagemann A N Shelling and P L PfefferldquoIsolation of genes differentially expressed in dominant andsubordinate bovine folliclesrdquo Endocrinology vol 144 no 9 pp3904ndash3913 2003

[30] F X Donadeu S N Schauer and S D Sontakke ldquoInvolvementof miRNAs in ovarian follicular and luteal developmentrdquo TheJournal of Endocrinology vol 215 no 3 pp 323ndash334 2012

[31] G Yao M Yin J Lian et al ldquoMicroRNA-224 is involved intransforming growth factor-120573-mediated mouse granulosa cellproliferation and granulosa cell function by targeting Smad4rdquoMolecular Endocrinology vol 24 no 3 pp 540ndash551 2010

[32] G Yan L Zhang T Fang et al ldquoMicroRNA-145 suppressesmouse granulosa cell proliferation by targeting activin receptorIBrdquo FEBS Letters vol 586 no 19 pp 3263ndash3270 2012

[33] A Dai H Sun T Fang et al ldquoMicroRNA-133b stimulatesovarian estradiol synthesis by targeting Foxl2rdquo FEBS Letters vol587 no 15 pp 2474ndash2482 2013

[34] Q Zhang H Sun Y Jiang et al ldquoMicroRNA-181a suppressesmouse granulosa cell proliferation by targeting activin receptorIIArdquo PLoS ONE vol 8 no 3 Article ID e59667 2013

[35] M Z Carletti S D Fiedler and L K Christenson ldquoMicroRNA21 blocks apoptosis in mouse periovulatory granulosa cellsrdquoBiology of Reproduction vol 83 no 2 pp 286ndash295 2010

[36] F Lin R Li Z X Pan et al ldquomiR-26b promotes granulosa cellapoptosis by targeting ATM during follicular atresia in porcineovaryrdquo PLoS ONE vol 7 no 6 Article ID e38640 2012


[37] X Yang Y Zhou S Peng et al ldquoDifferentially expressedplasma microRNAs in premature ovarian failure patients andthe potential regulatory function of mir-23a in granulosa cellapoptosisrdquo Reproduction vol 144 no 2 pp 235ndash244 2012

[38] Y Kitahara K Nakamura K Kogure and T Minegishi ldquoRoleofmicroRNA-136-3p on the expression of luteinizing hormone-human chorionic gonadotropin receptor mRNA in rat ovariesrdquoBiology of Reproduction vol 89 no 5 article 114 2013

[39] S Xu K Linher-Melville B B Yang D Wu and J Li ldquoMicro-RNA378 (miR-378) regulates ovarian estradiol production bytargeting aromataserdquo Endocrinology vol 152 no 10 pp 3941ndash3951 2011

[40] M Yin M Lu G Yao et al ldquoTransactivation of microRNA-383 by steroidogenic factor-1 promotes estradiol release frommouse ovarian granulosa cells by targeting RBMS1rdquo MolecularEndocrinology vol 26 no 7 pp 1129ndash1143 2012

[41] G Yao M Liang N Liang et al ldquoMicroRNA-224 is involved inthe regulation of mouse cumulus expansion by targeting Ptx3rdquoMolecular and Cellular Endocrinology vol 382 no 1 pp 244ndash253 2014

[42] X Li J Xu Y Li et al ldquoDissection of the potential characteristicof miRNA-miRNA functional synergistic regulationsrdquoMolecu-lar BioSystems vol 9 no 2 pp 217ndash224 2013

[43] M Yin X Wang G Yao et al ldquoTransactivation of microRNA-320 bymicroRNA-383 regulates granulosa cell functions by tar-geting E2F1 and SF-1 proteinsrdquo Journal of Biological Chemistryvol 289 no 26 pp 18239ndash18257 2014

[44] Y Wang J Ren Y Gao et al ldquoMicroRNA-224 targets sMADfamily member 4 to promote cell proliferation and negativelyinfluence patient survivalrdquo PLoS ONE vol 8 no 7 Article IDe68744 2013

[45] C M M Gits P F van Kuijk M B E Jonkers et al ldquoMiR-17-92 and miR-221222 cluster members target KIT and ETV1in human gastrointestinal stromal tumoursrdquo British Journal ofCancer vol 109 no 6 pp 1625ndash1635 2013

[46] R Feng Q Sang Y Zhu et al ldquoMiRNA-320 in the human fol-licular fluid is associated with embryo quality in vivo and affectsmouse embryonic development in vitrordquo Scientific Reports vol5 article 8689 2015

[47] D Salilew-Wondim I Ahmad S Gebremedhn et al ldquoTheexpression pattern of microRNAs in granulosa cells of subor-dinate and dominant follicles during the early luteal phase ofthe bovine estrous cyclerdquo PLoS ONE vol 9 no 9 Article IDe106795 2014

[48] S D Sontakke B T Mohammed A S McNeilly and FX Donadeu ldquoCharacterization of microRNAs differentiallyexpressed during bovine follicle developmentrdquo Reproductionvol 148 no 3 pp 271ndash283 2014

[49] B P Lewis I-H Shih M W Jones-Rhoades D P Bartel andC B Burge ldquoPrediction ofmammalianmicroRNA targetsrdquoCellvol 115 no 7 pp 787ndash798 2003

[50] M Kiriakidou P T Nelson A Kouranov et al ldquoA com-bined computational-experimental approach predicts humanmicroRNA targetsrdquo Genes amp Development vol 18 no 10 pp1165ndash1178 2004

[51] D W Huang B T Sherman and R A Lempicki ldquoSystematicand integrative analysis of large gene lists using DAVID bioin-formatics resourcesrdquo Nature Protocols vol 4 no 1 pp 44ndash572009

[52] A V Sirotkin ldquoTranscription factors and ovarian functionsrdquoJournal of Cellular Physiology vol 225 no 1 pp 20ndash26 2010

[53] P Shannon A Markiel O Ozier et al ldquoCytoscape a softwareEnvironment for integratedmodels of biomolecular interactionnetworksrdquo Genome Research vol 13 no 11 pp 2498ndash25042003

[54] V Nordhoff B Sonntag D von Tils et al ldquoEffects of theFSH receptor gene polymorphism pN680S on cAMP andsteroid production in cultured primary human granulosa cellsrdquoReproductive BioMedicine Online vol 23 no 2 pp 196ndash2032011

[55] D Li P Yang H Li et al ldquoMicroRNA-1 inhibits proliferation ofhepatocarcinoma cells by targeting endothelin-1rdquo Life Sciencesvol 91 no 11-12 pp 440ndash447 2012

[56] K J Livak and T D Schmittgen ldquoAnalysis of relative geneexpression data using real-time quantitative PCR and the 2(-DeltaDelta C(T))MethodrdquoMethods vol 25 no 4 pp 402ndash4082001

[57] H W Ahn R D Morin H Zhao et al ldquoMicroRNA transcrip-tome in the newborn mouse ovaries determined by massiveparallel sequencingrdquo Molecular Human Reproduction vol 16no 7 pp 463ndash471 2010

[58] B G Gasperin M T Rovani R Ferreira et al ldquoFunctionalstatus of STAT3 and MAPK31 signaling pathways in granulosacells during bovine follicular deviationrdquoTheriogenology vol 83no 3 pp 353ndash359 2015

[59] S Roy andT B Kornberg ldquoParacrine signalingmediated at cell-cell contactsrdquo BioEssays vol 37 no 1 pp 25ndash33 2015

[60] N Kaivo-Oja L A Jeffery O Ritvos and D G Motter-shead ldquoSmad signalling in the ovaryrdquo Reproductive Biology andEndocrinology vol 4 article 21 2006

[61] S A Pangas X Li E J Robertson and M M MatzukldquoPremature luteinization and cumulus cell defects in ovarian-specific Smad4 knockout micerdquo Molecular Endocrinology vol20 no 6 pp 1406ndash1422 2006

[62] Q Li S A Pangas C J Jorgez J M Graff M Weinstein andM M Matzuk ldquoRedundant roles of SMAD2 and SMAD3 inovarian granulosa cells in vivordquoMolecular and Cellular Biologyvol 28 no 23 pp 7001ndash7011 2008

[63] J Liu X Du J Zhou Z Pan H Liu and Q Li ldquoMicroRNA-26b functions as a proapoptotic factor in porcine folliculargranulosa cells by targeting Sma-and Mad-related protein 4rdquoBiology of Reproduction vol 91 no 6 article 146 2014

[64] G Shen Y Lin X Yang J Zhang Z Xu andH Jia ldquoMicroRNA-26b inhibits epithelial-mesenchymal transition in hepatocellu-lar carcinoma by targeting USP9Xrdquo BMC Cancer vol 14 article393 2014

[65] T Mishima T Takizawa S-S Luo et al ldquoMicroRNA (miRNA)cloning analysis reveals sex differences in miRNA expressionprofiles between adult mouse testis and ovaryrdquo Reproductionvol 136 no 6 pp 811ndash822 2008

[66] R Di J He S Song et al ldquoCharacterization and comparativeprofiling of ovarian microRNAs during ovine anestrus and thebreeding seasonrdquo BMC genomics vol 15 p 899 2014

[67] S K Tripurani C Xiao M Salem and J Yao ldquoCloning andanalysis of fetal ovary microRNAs in cattlerdquo Animal Reproduc-tion Science vol 120 no 1-4 pp 16ndash22 2010

[68] J Huang Z Ju Q Li et al ldquoSolexa sequencing of novel anddifferentially expressed microRNAs in testicular and ovariantissues in Holstein Cattlerdquo International Journal of BiologicalSciences vol 7 no 7 pp 1016ndash1026 2011

[69] J R Miles T G McDaneld R T Wiedmann et al ldquoMicroRNAexpression profile in bovine cumulus-oocyte complexes pos-sible role of let-7 and miR-106a in the development of bovine


oocytesrdquo Animal Reproduction Science vol 130 no 1-2 pp 16ndash26 2012

[70] P A C rsquot Hoen Y Ariyurek H H Thygesen et al ldquoDeepsequencing-based expression analysis shows major advancesin robustness resolution and inter-lab portability over fivemicroarray platformsrdquo Nucleic Acids Research vol 36 no 21article e141 2008

[71] A V Sirotkin D Ovcharenko R Grossmann M Laukova andM Mlyncek ldquoIdentification of microRNAs controlling humanovarian cell steroidogenesis via a genome-scale screenrdquo Journalof Cellular Physiology vol 219 no 2 pp 415ndash420 2009

[72] A V Sirotkin M Laukova D Ovcharenko P Brenaut andM Mlyncek ldquoIdentification of microRNAs controlling humanovarian cell proliferation and apoptosisrdquo Journal of CellularPhysiology vol 223 no 1 pp 49ndash56 2010

[73] C Yin J Zhang Z Shi W Sun H Zhang and Y FuldquoIdentification and expression of the target gene emx2 of miR-26a and miR-26b in Paralichthys olivaceusrdquo Gene vol 570 no2 pp 205ndash212 2015

[74] T Chiyomaru N Seki S Inoguchi et al ldquoDual regulationof receptor tyrosine kinase genes EGFR and c-Met by thetumor-suppressive microRNA-23b27b cluster in bladder can-cerrdquo International Journal of Oncology vol 46 no 2 pp 487ndash496 2015

[75] A Chinchilla E Lozano H Daimi et al ldquoMicroRNA profilingduring mouse ventricular maturation a role for miR-27 modu-latingMef2c expressionrdquo Cardiovascular Research vol 89 no 1pp 98ndash108 2011

[76] K Varendi A Kumar M-A Harma and J-O AndressooldquoMiR-1 miR-10b miR-155 and miR-191 are novel regulators ofBDNFrdquo Cellular and Molecular Life Sciences vol 71 no 22 pp4443ndash4456 2014

[77] N Nagpal H M Ahmad B Molparia and R KulshreshthaldquoMicroRNA-191 an estrogen-responsive microRNA functionsas an oncogenic regulator in human breast cancerrdquo Carcinogen-esis vol 34 no 8 pp 1889ndash1899 2013

[78] S E Palma-Vera S Sharbati and R Einspanier ldquoIdentificationof miRNAs in bovine endometrium through RNAseq andprediction of regulated pathwaysrdquo Reproduction in DomesticAnimals vol 50 no 5 pp 800ndash806 2015

[79] J C M Ricarte-Filho C S Fuziwara A S Yamashita ERezende M J Da-Silva and E T Kimura ldquoEffects of let-7 microRNA on cell growth and differentiation of papillarythyroid cancerrdquo Translational Oncology vol 2 no 4 pp 236ndash241 2009

[80] S Vimalraj and N Selvamurugan ldquoMicroRNAs expressionand their regulatory networks during mesenchymal stem cellsdifferentiation toward osteoblastsrdquo International Journal ofBiological Macromolecules vol 66 pp 194ndash202 2014

[81] J Lynch J Fay M Meehan et al ldquoMiRNA-335 suppressesneuroblastoma cell invasiveness by direct targeting of multiplegenes from the non-canonical TGF-120573 signalling pathwayrdquoCarcinogenesis vol 33 no 5 pp 976ndash985 2012

[82] T Suzuki K Mizutani A Minami et al ldquoSuppression of theTGF-1205731-induced protein expression of SNAI1 and N-cadherinby miR-199ardquo Genes to Cells vol 19 no 9 pp 667ndash675 2014

[83] A N Hirshfield ldquoDevelopment of follicles in the mammalianovaryrdquo International Review of Cytology vol 124 pp 43ndash1011991

[84] A J Hsueh E Y Adashi P B Jones and T H Welsh JrldquoHormonal regulation of the differentiation of cultured ovarian

granulosa cellsrdquo Endocrine Reviews vol 5 no 1 pp 76ndash1271984

[85] Q Song L Zhong C Chen et al ldquoMIR-21 synergizeswith BMP9 in osteogenic differentiationby activating theBMP9Smad signaling pathway in murine multilineage cellsrdquoInternational Journal of Molecular Medicine vol 36 no 6 pp1497ndash1506 2015

[86] H Liang C Xu Z Pan et al ldquoThe antifibrotic effects andmechanisms of microRNA-26a action in idiopathic pulmonaryfibrosisrdquoMolecular Therapy vol 22 no 6 pp 1122ndash1133 2014

[87] C Yu J-J Zhou andH-Y Fan ldquoStudying the functions of TGF-120573 signaling in the ovaryrdquo Methods in Molecular Biology vol1344 pp 301ndash311 2016

[88] S Li Q Fan S He T Tang Y Liao and J Xie ldquoMicroRNA-21 negatively regulates treg cells through a TGF-1205731smad-independent pathway in patients with coronary heart diseaserdquoCellular Physiology and Biochemistry vol 37 no 3 pp 866ndash8782015

[89] S D Fiedler M Z Carletti X Hong and L K ChristensonldquoHormonal regulation of microRNA expression in periovula-tory mouse mural granulosa cellsrdquo Biology of Reproduction vol79 no 6 pp 1030ndash1037 2008

Submit your manuscripts athttpswwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Anatomy Research International

PeptidesInternational Journal of


Hindawi Publishing Corporation httpwwwhindawicom

International Journal of

Volume 2014

Zoology


Molecular Biology International

GenomicsInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


BioinformaticsAdvances in

Marine BiologyJournal of



Signal TransductionJournal of


BioMed Research International

Evolutionary BiologyInternational Journal of



Biochemistry Research International

ArchaeaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Genetics Research International


Advances in

Virolog y

Hindawi Publishing Corporationhttpwwwhindawicom

Nucleic AcidsJournal of

Volume 2014

Stem CellsInternational



Enzyme Research



Microbiology


significant changes of follicular structure and functionrequiring accurate and coordinated adjustments to geneswhich have key roles in follicular selectionmaturation or thefollicle-luteal transition Any dysregulation in the expressionof these specific genes would be critical in determining thefate of DFs or SFs [8ndash11] In previous studies transcriptomeanalyses have identified some genes involved in folliculargrowth selection and maturation [12ndash14] However themolecular regulatory mechanisms at differential levels arestill unclear

Recently the posttranscriptional regulation dominatedby miRNAs has attracted extensive attention miRNAs regu-late gene expression via the combination of seed sequence andthe 31015840-untranslated region (UTR) of target mRNAs causingrepression of translation or degradation of the target mRNAsduring cell growth and differentiation [15] The expression ofmiRNA in the ovary varies with cell type function and stageof the estrous cycle miRNAs are involved in the formationof primordial follicles follicular recruitment and selectionfollicular atresia oocyte-cumulus cell interaction and GCfunction [1] Profiling studies of miRNA in ovarian tissueshave described the expression of miRNAs in the ovariesof various species [16ndash20] Conditional knockout (cKO) ofDicer1 from follicular GCs resulted in a number of ovarianfunctional defects including abnormal oocyte maturationdisrupted follicular development and ovulation increasedfollicular atresia and infertility [21ndash23] A single miRNAcould regulate follicle development during estrus cycle via acanonical pathway [24] in which the target gene of miRNAplays an important role Unsurprisingly many miRNAs alsocould target transcription factors (TFs) such as TGF-120573superfamily members follicle stimulating hormone receptor(FSHR) and luteinizing hormone receptor (LHR) whichhave been confirmed to have a connection with folliculardevelopment The abnormality of these molecules also led todysfunction of cellular communication and dysregulation ofnormal follicle development and recruitment [25ndash29] More-over several studies have demonstrated that the functions ofspecific miRNAs are implicated in different aspects of GCprocesses [30] such as proliferation [31ndash34] survival [35ndash37] terminal differentiation [38] steroidogenesis [31 33 3940] and cumulus expansion [41] in mammals For examplemiRNA-224 has been proved to be involved in transforminggrowth factor-beta-mediated mouse GCs proliferation andGC function by targeting smad4 [31] These results presentevidence that miRNA might be involved in the selectionof the DFs the mechanism of which has remained largelyelusive The complex nature of miRNA target interactionregulation and function however posed challenges forfunctional studies Whereas some miRNAs appear single-handedly to regulate specific signaling pathways most miR-NAs act in clusters and are fine tuners of cellular functionsIn most of previous studies results just demonstrated thefunction of a single miRNA in GCs In fact performingsignificant regulation of any biological process often resultsfrom complex regulating networks rather than one singlemiRNA Therefore an understanding of the mechanism ofaction of miRNA in follicular development requires globalcomprehension of the network of miRNA target interactions

within the milieux of other factors that dominate folliculardevelopment Hence profiling studies are important in orderto not only draw a spatial and temporal map of miRNAexpression in different follicles but also provide clues withregard to the function or regulation of miRNA

In this study according to 3 underused sequencingdatasets (GSE56002 GSE55987 and GSE54692) from GCs ofbovine we attempted to systematically dissect the complexsynergistic regulations of several functional miRNAs ratherthan a single miRNA in follicular development [42] basedon the networks of miRNAs-signal pathways and miRNAs-TFs AbundantmiRNAs and differentially expressedmiRNAswere identified and networks of miRNAs-signal pathwaysand miRNAs-TFs were constructed based on the correlationbetween miRNAs and predicted target genes Moreover bycalculating the degree of every node in networks hub playerswere identified to establish a centrical network from whichthe critical miRNAs pathways and TFs in the process offollicular development were identified The regulation of thesignificant miRNAs on hub genes would be further verifiedby RT PCR The results might provide novel insights intorevealing the potential mechanism ofmolecular regulation infollicular development in the context of miRNA synergisticregulatory networks

2 Materials and Methods

21 Differential Expression of miRNAs in GCs and DataNormalization A total of 64 differentially expressedmiRNAsin GCs were collected from the miRNA sequencing results ofSamuel Gebremedhnrsquos research group (GSE56002) [24] and52 ones from the study of another group Salilew-Wondimet al who also utilized Illumina small RNAseq (GSE55987)[47] Gebremedhn et al used miRDeep 2005 softwarepackage andDESeq2with a ldquohypothetical referencerdquo to screendifferentially expressed miRNAs in 6 ovarian follicle samples(3 biological replicates from DFs and others from SFs) at day19 of the estrous cycle in which the samples with externalsurface diameter ge 12mm were recognized as DFs whilethe ones le 11mm as SFs The study followed several cut-off criteria adjusted p value le 005 log2 fold change ge 1and false discovery rate (FDR) le 01 [24] Similarly Salilew-Wondim et al employed the analogous software andmethodsto analyze the differential expression of miRNAs under thesame criteria whichwere obtained from 12 granulosa samples(three biological replicates of GCs from SFs or DFs at day 3 orday 7 of the estrous cycle) [47] Briefly in this study follicleswith follicular diameter of 6mm (119899 = 43) were classifiedas SFs while follicles with a diameter of 8ndash10mm (119899 = 9)were considered as DFs at day 3 of the estrous cycle Onthe other hand at day 7 of the estrous cycle follicles witha diameter le 8mm (119899 = 58) were considered as SFs whilethose with 9ndash13mmdiameter (119899= 3) were categorized asDFsAlthough there are some biological differences between day3 and day 7 this did not exactly influence our analysis sincewhat we considered was the whole process of DFs and SFs Bycomparison abundantly expressed or dysregulated miRNAsin both datasets were dissected in this study Meanwhileanother dataset (GSE54692) which utilized microarray to




119875CT

= 1


(1)








2

















Upregulated miRNAs

miR-202 418 0002 998 0001miR-876-5p 379 0002 599 0001

















3 Results









(a)







6633387 3432217 05174DFs2 392924 255260DFs3 997715 428716


SFs1 861596 459794928373 467028 05031SFs2 939835 520377

SFs3 983688 420913

(b)











miR-191 BDNF






EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




119875CT

= 1


(1)








2

















Upregulated miRNAs

miR-202 418 0002 998 0001miR-876-5p 379 0002 599 0001

















3 Results









(a)







6633387 3432217 05174DFs2 392924 255260DFs3 997715 428716


SFs1 861596 459794928373 467028 05031SFs2 939835 520377

SFs3 983688 420913

(b)











miR-191 BDNF






EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology








Upregulated miRNAs

miR-202 418 0002 998 0001miR-876-5p 379 0002 599 0001

















3 Results









(a)







6633387 3432217 05174DFs2 392924 255260DFs3 997715 428716


SFs1 861596 459794928373 467028 05031SFs2 939835 520377

SFs3 983688 420913

(b)











miR-191 BDNF






EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology








(a)







6633387 3432217 05174DFs2 392924 255260DFs3 997715 428716


SFs1 861596 459794928373 467028 05031SFs2 939835 520377

SFs3 983688 420913

(b)











miR-191 BDNF






EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology






miR-191 BDNF






EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology





EGFR

PDGFRPDGF

TrkAB

GRB2 SOS Ras

G12 GaplmNF1p120GAP

RasGRFRasGRP


DAG

Rap1

PKC

CNrasGEF

RafBRaf1Mos


NIKIKK

TauSTMN1cPLA2


MEK1MEK2

ERK

PTP MKPPPP3C

CREBElk-1Sapla SRF

DNA

DNA

DNA

DNA

DNAc-fos



TNFIL1

FASLTGFB

TNFRIL1R

TGFBRCD14

LPSDNA damage

CASP

TRAF2

TAB1TAB2ECSITTRAF6

GADD45

MST12

GCK

LZKMUKMLTKASK2

ASK1

TAK1

PP2CBMEKK4

TAO12

PP5

MKK3

MKK6p38

PRAKMAFKAFK

MSK12Cdc25B

NLK


ATF-2Elk-1p53

SaplaGADD153

MAXMEF2C

HSP27

CREB



ApoptosisCellcycle

GLK

Cdc42Rac MEKK23

ARRBJIP3

CrkII

GSTHSP72

EvilFLNA

AKT

JIP12

HGKHPK1

MKK4

MKK7

MEKK1

JNKMLK3



and other stress

ERK5 pathway



MEK5 ERK5 Nur77



+p

+p

+p +p

+p

+p

+p+p+p

+p+p

+p+p

+p

+p

+p

+p

+p

+p

+p +p

+p

+p

+p

+p

+p

+p+p+p

+p

+p+p

+p

+p+p

+p

minusp minusp

minuspminusp

minusp

minuspminuspminusp

minuspminusp

minuspTp12Cot

PKA

MKPPTP

PP2CA

DAXX

PAK12

FAS


Ca2+



c-Myc

Scaffold















BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology











BP






CC






MF








BMPRIBMPRIIDAN BMP

Smadl58


DNA

DNA

DNA

DNA

DNA

DNAId



TNFSmad67 Rbx1

Cul1THBS1

LTBP1 BAMBISmurf12


Smad23

SARA Smad4


and corepressors

p107E2F45

DP1c-Myc



Apoptosis

Ubiquitinmediated

proteolysis TGIF




RhoAPP2A

ROCK1

Lefty

FST Activin

Nodal

BAMBI

ActivinRIActivinRII

NodalRINodalRII

Smad23

Smad23

Smad67 Smad4

Smad4

Pitx2




+p

+p

+p

+p

+p

+p

minusp

+u +u


IFN

Skp1

p70S6K




SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


SRF

FOXO3CEBPB

STAT3

FOXO4

HIF1A

GATA6

FOXO1

NFYANtrk2

Ngf

Ptch1

HnrnpkNCOR1

BRCA2

POU5F1MIDN

Elf1Taf4b

BRCA1

Ets1

GATA4STAT1

LHX8FOXL2

SMAD1SMAD2

SMAD3SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409a

miR-335


miR-21-3p

miR-191

miR-214

miR-708

let-7i

let-7a-5plet-7f

miR-224

(a)

NFYA

Ntrk2

Ngf

Ptch1

HnrnpkEts1

SMAD2

SMAD3

SMAD4

SMAD5

Kit

miR-221

miR-26a

miR-409amiR-335

miR-10b

miR-27b

miR-34c

miR-21-3pmiR-214

miR-708

let-7i

let-7a-5p

let-7f

miR-224

(b)

FOXO4

BRCA1Est1

NR4A1 Ptch1

MSX1

SOHLH2Kit

Figla SMAD4

SMAD1

HIF1A

FOXO3

Taf4b

SMAD5

LHX8SMAD2

NANOG MIDN

CEBPB

FOXL2

Gli1 SOX2 NCOR1

STAT1

GATA6

Hnrnpk

Ntrk2

NFYA

SRF Elf1

SMAD3

NR5A1STAT3

miR-1275miR-144-3p

miR-876-5p

miR-876-3p

miR-202

miR-4279miR-3178

miR-625-3p

miR-498

(c)

NFYA

Ntrk2

Ptch1

Hnrnpk

Ets1

miR-1275

miR-876-5p

miR-876-3p

miR-202

miR-625-3p

miR-4279

GATA6

BRCA1

HIF1A

SMAD2

MIDN STAT3

NR5A1

SRF

STAT1

miR-144-3p

miR-3178

FOXO3

miR-498

(d)





Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


Adherens junction



miR-3178

Endocytosis

miR-876-3p

miR-10b

miR-625-3p

HTLV-I infection


Pancreatic cancer

Colorectal cancer


miR-498

miR-4279

miR-409a

miR-21-3p

miR-224miR-26a

miR-27b


Cell cycle

Pathways in cancer

SMAD2








HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


HumanChimpRabbit

CowmiR-26amiR-26b






--U-----G---------UAGU U G G G A AGU -----

(a)

lowastlowast

lowast

miR-26amiR-26b

minus minus

minus minus

+

+

0

1

2

3

Relat

ive e

xpre

ssio

nU

6


(b)

lowastlowastlowast

00

05

10

15

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(c)

lowast

lowastlowastlowast

0

1

2

3

4

Relat

ive e

xpre

ssio

n

-act

in

minus minus

minus minus

+

+


smad2

(d)

lowast

minus minus

minus minus

+

+


00

05

10

15

20

Relat

ive e

xpre

ssio

n

-act

in

smad2

(e)




4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology



4 Discussion








5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




5 Conclusions


Disclosure


Competing Interests


Acknowledgments


References







































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology

MicroRNA Mediating Networks in Granulosa Cells Associated with...

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Transcript of MicroRNA Mediating Networks in Granulosa Cells Associated with...